However, gathering and analyzing the data from these sensors has always been a challenge. After each training session finished, Neal Henderson had to plug the head unit of each bike into his PC, download the data, manually slice it into half-second intervals, match those intervals to the events that took place during the session (for example, when each rider was pulling, versus when they were exchanging or pursuing), and then calculate a variety of key metrics. This took at least one hour per rider—and even when all four riders’ data was ready, there was still the task of collating and comparing individual results to get a 360-degree view of team performance.
Andy Sparks comments: “Neal would regularly be staying up past midnight each day during a training camp. He’s an incredibly valuable and talented coach, and we share him with several other cycling teams—so while he’s with us, we want him to be interacting with our riders, rather than spending all his time crunching the numbers on a computer.”
Neal Henderson adds: “The time taken to get the data also had an impact on how effective the analysis was as a coaching tool. If you’re talking to a rider about what they did on the track yesterday, that’s much less immediate and powerful than if you can talk to them while their legs are still burning from the session!”
Finding a better solution with the Internet of Things
Working with IBM jStart, the Women’s Team Pursuit team is now harnessing emerging technologies to solve its analytics challenge. Instead of manually extracting the data from the power meters and sensors after each training session, the data is automatically collected by an Android phone in the rider’s pocket, and transmitted to the cloud, where it is stored and analyzed as soon as the session finishes. Within seconds, the results are then sent back from the cloud to the coaches’ tablets, in the form of a summary dashboard that presents metrics such as W-prime depletion and matches burned in an intuitive graphical format.
From a technical perspective, IBM Watson™ Internet of Things Platform acts as a cloud integration hub, receiving the data and directing it to other components of the solution. For example, the raw data from the sensors passes through a Node-RED storage flow to an IBM Cloudant® database, which is used to supply the summary dashboard, and also feed a Jupyter Notebook for more complex analysis by the team’s data scientists.
Other components, which will be coming online soon, include the use of IBM Analytics for Apache Spark to calculate metrics in real time. This will allow the team’s coaches to monitor performance not only after the training session, but while it is still in progress—for example, during each exchange, the coaches will be able to see whether a match was burned. The team even plans to introduce smart glasses, which will provide a personalized head-up display of whichever key metrics are most useful for each of the riders, while they are actually on the track.
Andy Sparks comments: “We always had a vision that this kind of thing was possible, and IBM jStart is helping us turn it into a reality. We have been so impressed with the jStart team’s ability to orchestrate all of these emerging technologies to build a solution that delivers exactly what we need, in seconds.”
Neal Henderson comments: “The ability to get hold of the data immediately after the training session has finished has completely changed my relationship with the team. I’m spending much more time with the riders and the other coaches, and because we can all see the data instantly, it’s much easier to identify problems, make adjustments, and reinforce winning behaviors that they can take into the next session.”
On track for victory
The team began using the solution shortly before its victory at the 2016 World Championships in London, and will continue using it at training camps in the lead up to the 2016 Olympic Games in Rio.
“This year has already been one of the most successful in our history—at the World Championships, we won the qualifier by four seconds, beat the previous US record by six seconds, and took the gold medal in the final,” says Andy Sparks. “Although we only started using the IBM solution a few weeks before the event, we immediately saw its potential to help us identify and fast-track tactical and technical improvements. It’s the most important technology project we have worked on this year, and we see it as a key tool in our preparations for Rio.”
Neal Henderson adds: “We always aim to train as hard as possible, to make racing as easy as possible. The solution helps us show our riders exactly how effectively they’re working, so they can see that what we’re asking them to do in competition isn’t impossible—it’s what they’ve trained for, and what they’ve achieved 100 times before in training.
“The ability to instantly quantify and reinforce the positive gains made during each session really helps lower the stress of competing in a big race, and helps the riders focus on executing the performance that they already know they are capable of.”
Although certain elements of the solution cannot be used during competitive races, USA Cycling believes that the dashboards could become even more valuable during the intense time-pressure of a competitive event.
Neal Henderson says: “When you’re at an event, there’s only a very short window between the races—there just isn’t time to spend four or five hours pulling data together, and even if there were, the riders need some downtime instead of worrying about what happened in the last race. The big advantage of instant analytics is that we will be able to give the riders a quick debrief after the first race, advise them on tactics for the next one, and then just let them relax and recover.”
Andy Sparks concludes: “The whole engagement with IBM jStart has been in line with our culture of excellence at USA Cycling. The jStart team have the same principles—everything they do is delivered to the highest possible standard, and we’re proud to be working with them to push the boundaries of what is possible in cycling technology.
“Compared to other big cycling nations, our budget is very tight—we rely 100 percent on sponsorship, whereas many teams receive large amounts of government funding. Yet we’re showing that we can compete successfully at international level. IBM deserves credit for helping us train smarter and free our riders to execute successfully at the major events. Of all the technology projects we’ve worked on this year, the IBM jStart project has made the biggest contribution to achieving our goals.”